1. Technical Field
The present invention relates generally to MR angiography. Specifically, the present invention displays MR angiograpic data that illustrates blood vessels which exists at different depths within a patient, while maintaining the contrast of the image.
2. Description of the Related Art
Before MR angiography was developed, x-ray angiography was used to image blood vessels within the human body. To create these images, a substance that was highly absorptive of x-rays was injected into the patient""s blood vessels. A film was then exposed to x-rays that were passed through the patient""s body, and the blood vessels were clearly shown on the film, due to the injected substance. Once the film was developed, blood vessels within the patient appeared as semitransparent vessels. The resulting images also displayed blood vessels that were located at different depths within the patient. The areas where two vessels overlapped was darker than either of the vessels themselves, and helped to convey information relating to the depth at which various vessels were located in the patient.
Angiographic images can also be created using nuclear magnetic resonance (NMR) techniques. MR angiographic images can illustrate vessels within a patient""s body, but the contrast of the vessels relative to the surrounding tissue is not nearly as great when compared to the contrast achieved using x-ray angiography. This lack of contrast makes distinguishing the vessels from the surrounding tissue difficult.
MR angiographic data consists of many two dimensional (2D) image, which are also known as slices, placed together to form a three dimensional (3D) set of data which represents some volume of interest within the patient. Typically, within this volume of interest, the vessels represent the most intense images. However, as described above, their intensity is not much greater than that of the surrounding tissue.
Today, the most commonly used technique to separate the data representing the vessels from the data representing the surrounding tissue is known as the maximum intensity projection (MIP) method. This method creates a 2D image of the vessels contained in the 3D array of angiographic data. To construct the 2D image, the MIP method constructs a series of rays extending through the 3D array of data, with one ray for every pixel to be contained in the 2D image, and with every data point within the 3D array being intersected by a single ray. Then, for a given ray, the MIP method selects the single most intense data point intersected by the ray, and uses this point to control the brightness of the pixel associated with that ray. This process is repeated for each ray to create a 2D images composed of the pixels associated with each ray.
For example, the 3D array of NMR data may consist of 256xc3x97256xc3x97256 array of data values. The 2D image representing this 3D array may contain 256xc3x97256 pixels. To construct the 2D image, 256xc3x97256 rays (one for each pixel in the 2D image) are extended through the 3D array of data, with each ray intersecting 256 data points within the 3D array. For each ray, the single most intense data point out of the 256 data points intersected by the ray is selected, and this single data point is used to control the display of the pixel in the 2D image.
There are obvious deficiencies with this method. Perhaps the single most important deficiency is that only one out of every 256 data points within the 3D array is used to construct the 2D image. Thus, 255 out of the 256 data points within the 3D array are discarded and not used in constructing the 2D image. Important details and valuable information are lost in not using the vast majority of data points.
Another deficiency in the MIP method is that no information relating to vessels lying at different depths within the 3D array is shown. For example, if two vessels overlap each other, with one vessel being located in front of the other vessel from the point of view of the 2D image, the MIP method will only be able to show one of these vessels, since only one data point is selected for each ray traversing through the 3D array of data. Since only a single data point is selected, two vessels existing at different depths within the patient and which overlap will only be represented by a single data point. Thus, either the vessel in the foreground or the vessel in the background will be represented, but not both.
Other methods that create 2D images from the 3D array of data take into account all of the data points within the 3D array, unlike the MIP method. However, the majority of the data points within the 3D array represent tissue other than the blood vessels of interest. When the data points within the 3D array of data representing the background tissue are combined with the data points representing the blood vessels of interest, the large amount of data points representing background tissue can overwhelm the relatively few data points which represent the blood vessels of interest. The resulting image may contain details showing how blood vessels at different depths overlap, but much of the details surrounding the blood vessels will be xe2x80x9cwashed outxe2x80x9d due to the inclusion of the background tissue.
Therefore, what is needed is a method that can create a 2D image from a 3D array of angiographic data which shows blood vessels existing at different depths within the 3D array of data. Such a method should also clearly show the details of these vessels, and be able to separate the data points that represent the blood vessels from the surrounding background tissue.
When characterized as a method, the present invention creates detailed 2D images from 3D arrays of angiographic data. First, a 3D array of angiographic data is acquired. Next, one determines from which perspective they wish to view the 3D data. After the perspective is selected, for each pixel in the 2D image to be created, an imaginary ray is extended through the 3D array, according to the perspective from which the 2D image is being rendered. For each ray, the n most intense data points intersected by that ray are selected and summed together. Finally, the 2D image is created on a pixel by pixel basis, with each pixel being displayed according to the sum of the n most data points intersected by the ray associated with that pixel.